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Mathews Madola mm87@gre.ac.uk University of Greenwich Natural Resources Institute

Transaction Costs and Agricultural Commercialisation: The Role of Market Institutions & Farmer Organisations in Improving Market Access and their Effects on Pro-Poor Growth in Malawi. Mathews Madola mm87@gre.ac.uk University of Greenwich Natural Resources Institute. Outline.

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Mathews Madola mm87@gre.ac.uk University of Greenwich Natural Resources Institute

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  1. Transaction Costs and Agricultural Commercialisation: The Role of Market Institutions & Farmer Organisations in Improving Market Access and their Effects on Pro-Poor Growth in Malawi Mathews Madola mm87@gre.ac.uk University of Greenwich Natural Resources Institute

  2. Outline • Background and Motivation • Problem Statement • Key Research Questions • Conceptual Framework (Institutional Analysis) • Methodology and Data Collection • Preliminary Results • Emerging Conclusions

  3. Background • There is a growing trend towards the promotion of farmer organisations as a poverty reduction strategy to improve smallholders access to inputs, extension services and output markets. • It is therefore important understand benefits and effects of this institutional arrangement. • Most studies have concentrated on the effects of contract farming

  4. Problem Statement • Farmers no longer assured of ready markets for their products. • Face volatile market prices in place of a previous system of stable markets (state-guaranteed prices) • Decreased access to credit and inputs. • Negatively affecting output and productivity

  5. Research Questions • The Key research questions are: • What are the determinants of participation in farmer organisations? • What is the impact of participation on household income (performance ) ?

  6. Conceptual Framework and Institutional Analysis • We develop the conceptual framework following Williamson (1991) and link it to an institutional analysis to identify the factors determining the current organisational form of production and marketing in the cotton sub-sector in Malawi. • The analytical model follows the ones used in applied work in transaction costs (e.g. Doward, 2001) • The likelihood of observing a particular market institution is a function of certain properties of the underlying transaction • Can be expressed as Y=Ω[X], where Y is a vector of alternative marketing arrangements i.e. spot marketing, contract marketing and collective marketing (farmer organisations)

  7. Conceptual Framework (cont’d) • X is a vector of transaction characteristics that affect transaction costs i.e. asset specificity, uncertainty, complexity and frequency of transactions. • The level of X is influenced by production, marketing characteristics, and the economic and political environment. • Framework the used to explain how these factors affect transaction costs and choice of organisational form

  8. Transaction Costs and Marketing Institutional Arrangements

  9. Methodology & Data Collection • Used a structured questionnaire • Interviewed smallholder farmers growing cotton 170 respondents (83 participants and 87 non participants). • Also did some key informant interviews

  10. Distribution of the Sample

  11. Methodology : Determinants of Participation • We will estimate the following probit model : m • PARTi = φ0 + ∑φjxj +e2 j=1 • xj is a vector of exogenous variables assumed to influence the participation decision; φjs represents estimated marginal effects of the determinants of participation; PART is a dummy variable that takes a value of one or zero

  12. Impact of Participation on Incomes (Performance) • We will use propensity score matching methods applied in programme evaluation. • Use four matching methods to enhance the robustness of our comparisons • Nearest Neighbor • Radius • Kernel • Stratification matching • Our aim is to determine whether participating households have significantly higher crop and household incomes than non-participants.

  13. Endogenous Switching Regression • We also estimate the endogenous switching regression model to take into account selection bias • We use this model to examine how farmers characteristics affect their decisions to participate in a farmer organisations and their income (performance) with or without the farmer organisation. • We will also compare farmers expected performance (income) with the farmer organisation and without the farmer organisation • The following model describes farmers’ choices about participating in a farmer organisations and their performance with and without a farmer organisation

  14. Impact of Participation (cont’d) • If δZi + ut> 0 , farmer i chooses to join a farmer organisation, described by Ii =1 (A) • If δZi + ut ≤ 0 , farmer i chooses not to join a farmer organisation, described by Ii =0 • Then income (performance) equations associated with each alternative can be expressed as • Participants :ln y1i = x1ß1 + et0 if j = 1 (B) • Non-participants :ln y0i = x0ß0 + et1 if j = 0 (C) • Zi is a vector of farmers characteristics that affect decisions to participate in farmer organisation • ln y01 and ln y0i are natural logs of income (performance) for participants and non-participants, respectively; δ, ß’s are unknown parameters • Assume that ut , et0 and et1 are three random terms that follow a trivariate normal distribution • The methodology involves estimating system of equations (A), (B) and (C) equations by FIML as suggested by (Loskin and Sajaia, 2004)

  15. Results-Comparison of Means

  16. Initial Results from Probit Model • The availability of alternative sources of income reduces the likelihood of participation. Other cash crops income that are more lucrative and business income are negatively related to the likelihood of participation although the business income is not statistically significant • Household size is positively related to participation in a farmer organisation • Households with more educated household heads are less likely to participate in farmer organisations. • The ownership of assets value of agricultural tools is positively related to probability of participation while land is negatively related to participation. • Having a friend who is a member of a farmer organisation (social capital), the more likely the household will participate.

  17. Emerging Conclusions • Initial analysis indicates that FO leads to higher income (performance of participants) . • Other benefits of participation include • reliable markets, stable prices and reduced uncertainty • The social capital in farmer organisations has reduced the problems of writing, enforcing contracts prevalent in Malawi (culture of wilful default)

  18. Thank you for your attention!

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